{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T05:47:02Z","timestamp":1790056022236,"version":"4.0.1"},"reference-count":38,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"13","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circulation"],"published-print":{"date-parts":[[2021,3,30]]},"abstract":"<jats:sec>\n            <jats:title>Background:<\/jats:title>\n            <jats:p>Heart rate\u2013corrected QT interval (QTc) prolongation, whether secondary to drugs, genetics including congenital long QT syndrome, and\/or systemic diseases including SARS-CoV-2\u2013mediated coronavirus disease 2019 (COVID-19), can predispose to ventricular arrhythmias and sudden cardiac death. Currently, QTc assessment and monitoring relies largely on 12-lead electrocardiography. As such, we sought to train and validate an artificial intelligence (AI)\u2013enabled 12-lead ECG algorithm to determine the QTc, and then prospectively test this algorithm on tracings acquired from a mobile ECG (mECG) device in a population enriched for repolarization abnormalities.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods:<\/jats:title>\n            <jats:p>Using &gt;1.6 million 12-lead ECGs from 538 200 patients, a deep neural network (DNN) was derived (patients for training, n = 250 767; patients for testing, n = 107 920) and validated (n = 179 513 patients) to predict the QTc using cardiologist-overread QTc values as the \u201cgold standard\u201d. The ability of this DNN to detect clinically-relevant QTc prolongation (eg, QTc \u2265500 ms) was then tested prospectively on 686 patients with genetic heart disease (50% with long QT syndrome) with QTc values obtained from both a 12-lead ECG and a prototype mECG device equivalent to the commercially-available AliveCor KardiaMobile 6L.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results:<\/jats:title>\n            <jats:p>In the validation sample, strong agreement was observed between human over-read and DNN-predicted QTc values (\u22121.76\u00b123.14 ms). Similarly, within the prospective, genetic heart disease\u2013enriched dataset, the difference between DNN-predicted QTc values derived from mECG tracings and those annotated from 12-lead ECGs by a QT expert (\u22120.45\u00b124.73 ms) and a commercial core ECG laboratory [10.52\u00b125.64 ms] was nominal. When applied to mECG tracings, the DNN\u2019s ability to detect a QTc value \u2265500 ms yielded an area under the curve, sensitivity, and specificity of 0.97, 80.0%, and 94.4%, respectively.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions:<\/jats:title>\n            <jats:p>Using smartphone-enabled electrodes, an AI DNN can predict accurately the QTc of a standard 12-lead ECG. QTc estimation from an AI-enabled mECG device may provide a cost-effective means of screening for both acquired and congenital long QT syndrome in a variety of clinical settings where standard 12-lead electrocardiography is not accessible or cost-effective.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/circulationaha.120.050231","type":"journal-article","created":{"date-parts":[[2021,2,1]],"date-time":"2021-02-01T10:09:24Z","timestamp":1612174164000},"page":"1274-1286","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":123,"title":["Artificial Intelligence\u2013Enabled Assessment of the Heart Rate Corrected QT Interval Using a Mobile Electrocardiogram Device"],"prefix":"10.1161","volume":"143","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5871-0265","authenticated-orcid":true,"given":"John R.","family":"Giudicessi","sequence":"first","affiliation":[{"name":"Clinician-Investigator Training Program (J.R.G.), Mayo Clinic, Rochester, MN."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1203-0621","authenticated-orcid":true,"given":"Matthew","family":"Schram","sequence":"additional","affiliation":[{"name":"AliveCor Inc., Mountain View, CA. (M.S., C.D.G., J.B.S., D.E.A.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3635-2003","authenticated-orcid":true,"given":"J. Martijn","family":"Bos","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine; Windland Smith Rice Sudden Death Genomics Laboratory, Department of Molecular Pharmacology and Experimental Therapeutics (J.M.B., M.J.A.), Mayo Clinic, Rochester, MN."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Conner D.","family":"Galloway","sequence":"additional","affiliation":[{"name":"AliveCor Inc., Mountain View, CA. (M.S., C.D.G., J.B.S., D.E.A.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacqueline B.","family":"Shreibati","sequence":"additional","affiliation":[{"name":"AliveCor Inc., Mountain View, CA. (M.S., C.D.G., J.B.S., D.E.A.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8365-1375","authenticated-orcid":true,"given":"Patrick W.","family":"Johnson","sequence":"additional","affiliation":[{"name":"Department of Health Sciences Research (Biomedical Statistics and Informatics), Mayo Clinic, Jacksonville, FL (P.W.J., R.E.C.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0818-273X","authenticated-orcid":true,"given":"Rickey E.","family":"Carter","sequence":"additional","affiliation":[{"name":"Department of Health Sciences Research (Biomedical Statistics and Informatics), Mayo Clinic, Jacksonville, FL (P.W.J., R.E.C.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Levi W.","family":"Disrud","sequence":"additional","affiliation":[{"name":"Division of Heart Rhythm Services, Windland Smith Rice Genetic Heart Rhythm Clinic (L.W.D., Z.I.A., P.A.N., P.A.F., M.J.A.), Mayo Clinic, Rochester, MN."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Kleiman","sequence":"additional","affiliation":[{"name":"eResearch Technology Inc, Philadelphia, PA (R.K.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9706-7900","authenticated-orcid":true,"given":"Zachi I.","family":"Attia","sequence":"additional","affiliation":[{"name":"Division of Heart Rhythm Services, Windland Smith Rice Genetic Heart Rhythm Clinic (L.W.D., Z.I.A., P.A.N., P.A.F., M.J.A.), Mayo Clinic, Rochester, MN."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4308-0456","authenticated-orcid":true,"given":"Peter A.","family":"Noseworthy","sequence":"additional","affiliation":[{"name":"Division of Heart Rhythm Services, Windland Smith Rice Genetic Heart Rhythm Clinic (L.W.D., Z.I.A., P.A.N., P.A.F., M.J.A.), Mayo Clinic, Rochester, MN."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul A.","family":"Friedman","sequence":"additional","affiliation":[{"name":"Division of Heart Rhythm Services, Windland Smith Rice Genetic Heart Rhythm Clinic (L.W.D., Z.I.A., P.A.N., P.A.F., M.J.A.), Mayo Clinic, Rochester, MN."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David E.","family":"Albert","sequence":"additional","affiliation":[{"name":"AliveCor Inc., Mountain View, CA. 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